Simple repository to explore and show data about the new pandemic virus Corona Virus.
World Data at: https://github.com/CSSEGISandData/COVID-19
Brazil Data at: https://github.com/wcota/covid19br
Brazil Population and other informations: https://www.ibge.gov.br/estatisticas/sociais/populacao.html
World Population: https://www.worldometers.info/world-population/population-by-country/
Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand
In case you are running the notebook, do not forget to give a:
$> pip install -r requirements.txt
Download Firefox webdriver from https://github.com/mozilla/geckodriver/releases/tag/v0.26.0 to save the heatmap at the end.
Last run: 2020-06-27 09:50:43.311181
-------------------- Confirmed cases stats: -------------------- Mortality Rate : 5.12 % Recovered Rate : 50.33 % Confirmed Cases: 9430384 Recovered : 4746118 Total Death : 482752 -------------------- World Population stats: -------------------- Confirmed Cases: 0.12418 % Mortality Rate : 0.00636 %
Country Confirmed Deaths Recovered Mortality % Population Density/Pop Urban/Pop % Mortality/Pop %
United States 2381361 121979 656161 5.12 331002651 36 0.83 0.03685
Brazil 1188631 53830 660469 4.53 210147125 25 0.88 0.02562
Russia 606043 8503 368222 1.40 145934462 9 0.74 0.00583
India 473105 14894 271697 3.15 1380004385 464 0.35 0.00108
United Kingdom 308337 43165 1345 14.00 67886011 281 0.83 0.06358
Peru 264689 8586 151589 3.24 32971854 26 0.79 0.02604
Chile 254416 4731 215093 1.86 19116201 26 0.85 0.02475
Spain 247086 28327 150376 11.46 46754778 94 0.80 0.06059
Italy 239410 34644 186111 14.47 60461826 206 0.69 0.05730
Iran 212501 9996 172096 4.70 83992949 52 0.76 0.01190
France 197885 29734 75251 15.03 65273511 119 0.82 0.04555
Mexico 196847 24324 148487 12.36 128932753 66 0.84 0.01887
Pakistan 192970 3903 81307 2.02 220892340 287 0.35 0.00177
Germany 192871 8928 176422 4.63 83783942 240 0.76 0.01066
Turkey 191657 5025 164234 2.62 84339067 110 0.76 0.00596
Saudi Arabia 167267 1387 112797 0.83 34813871 16 0.84 0.00398
Bangladesh 122660 1582 49666 1.29 164689383 1265 0.39 0.00096
South Africa 111796 2205 56874 1.97 59308690 49 0.67 0.00372
Canada 104087 8544 66533 8.21 37742154 4 0.81 0.02264
Qatar 90778 104 73083 0.11 2881053 248 0.96 0.00361
The bellow graphics show the evolution of the desease over time for some countries.
Bellow some graphics in log scale of Confirmed cases for the above countries.
Predicting the pandemic of Corona Virus is hard, bellow is a simple demonstration of curve fitting, using 2 types (exponential and sigmoid) for estimation.
Another problem is not knowing the actual mortality for the disease.
The mortality for Covid-19 are said to be something like 3.8%, but previous calculations (based on data from China) put the mortality to be somthing like 2%... if this is truth, and looking at the mortality for Brazil, US and Italy, we should be able to extrapolate and calculate the possible real number of people who has the disease (been asyntomatic or not).
BRAZIL -------------------- Taking into account 3.8%, means that it should have 1416578 cases. Taking into account 2%, means that it should have 2691500 cases.
UNITED STATES -------------------- Taking into account 3.8%, means that it should have 3209973 cases. Taking into account 2%, means that it should have 6098950 cases.
ITALY -------------------- Taking into account 3.8%, means that it should have 911684 cases. Taking into account 2%, means that it should have 1732200 cases.
Simple compilation of cases in United States.
Province_State Confirmed Deaths Mortality %
New York 389666 31257 8.02
California 195925 5725 2.92
New Jersey 169892 13076 7.70
Illinois 138540 6770 4.89
Texas 128132 2270 1.77
Florida 109014 3281 3.01
Massachusetts 107611 7937 7.38
Pennsylvania 87685 6518 7.43
Georgia 69381 2698 3.89
Michigan 68555 6114 8.92
Simple compilation of cases in Brazil.
For the entire Brazil, as of today, we have the following numbers:
Mortality Rate : 4.38 % Total Death : 56110 Confirmed Cases : 1280513 Mortality Rate/Pop : 0.0267 %
But, the story can't be told by the entire country, one must take into account, each state of the federation. Let's show data for each state in the federation.
UF Total Cases Deaths Mortality % Population Mortality/Pop %
São Paulo 258508 13966 5.40 45919049 0.03041
Rio de Janeiro 108497 9587 8.84 17264943 0.05553
Ceará 105270 5962 5.66 9132078 0.06529
Pará 99313 4834 4.87 8602865 0.05619
Maranhão 76698 1906 2.49 7075181 0.02694
Amazonas 68220 2739 4.01 4144597 0.06609
Bahia 56422 1642 2.91 14873064 0.01104
Pernambuco 55804 4610 8.26 9557071 0.04824
Paraíba 42832 864 2.02 4018127 0.02150
Espírito Santo 41652 1507 3.62 4018650 0.03750
Each state tells a different story, but what about the capitals for some of those states?
Bellow some possible projections for the next 10 days of infected people for each capital showed above.
Deaths in each capital are growing... let's visualize how deaths are spread across some cities.
City Total Cases Deaths Mortality %
São Paulo/SP 121163 6880 5.68
Rio de Janeiro/RJ 55152 6264 11.36
Fortaleza/CE 34027 3212 9.44
Manaus/AM 26783 1747 6.52
Salvador/BA 27666 1046 3.78
Brasília/DF 41326 532 1.29
Curitiba/PR 3093 122 3.94
Belo Horizonte/MG 4977 109 2.19
Porto Alegre/RS 2383 76 3.19
Much has been talked about that people in Brazil are young, so there's little risk for the population... but if we take into account that Brazil population is one of the biggest in the world and calculating death or hospitalization based on data provided by Imperial College and China CDC, Brazil could have more than 50k deaths. This is a simplistic view... it should take into account comorbidities to calculate those numbers.
CDC China:
--------------------
Age (years) Fatality Ratio %
0-9 0.0
10-19 0.2
20-29 0.2
30-39 0.2
40-49 0.4
50-59 1.3
60-69 3.6
70-79 8.0
80 14.8
Imperial College:
--------------------
Age (years) % symptomatic cases (hospitalisation) % hospitalised cases requiring critical care Fatality Ratio %
0-9 0.1 5.0 0.002
10-19 0.3 5.0 0.006
20-29 1.2 5.0 0.030
30-39 3.2 5.0 0.080
40-49 4.9 6.3 0.150
50-59 10.2 12.2 0.600
60-69 16.6 27.4 2.200
70-79 24.3 43.2 5.100
80 27.3 70.9 9.300
Given the above values (from Imperial College and CDC China) lets do a projection of the possible # of deaths in each Age group and given a possible interval of deaths that may occur.
Age Population # Hospitalization # Critical Care # Deaths (Imperial College) # Deaths (China CDC)
0-9 29340464 29341 1468 1 0
10-19 31089140 93268 4664 1 10
20-29 34324757 411898 20595 7 42
30-39 34130660 1092182 54610 44 110
40-49 28689589 1405790 88565 133 355
50-59 23477440 2394699 292154 1753 3799
60-69 16173590 2684816 735640 16185 26484
70-79 8654924 2103147 908560 46337 72685
80 3492257 953387 675952 62864 100041
Name Min. Deaths Max. Deaths
Imperial College 25465 229185
CDC China 40705 366346
Mean(Imperial + CDC China) 33085 297765
Age Min. Deaths Max. Deaths
0-9 0 0
10-19 1 9
20-29 4 44
30-39 15 138
40-49 48 439
50-59 555 4996
60-69 4266 38402
70-79 11902 107119
80 16290 146614